Data Science & AI Lead in London

Overview Join us as a Data Science & AI Lead In this key role, you\u0027ll lead Data Science and AI capabilities for the Economic Crime Hub, designing, building, and scaling production-grade models, AI systems, and automated decisioning solutions.

You\u0027ll own the end-to-end lifecycle of models and AI agents, ensuring decisions are executed safely, consistently, and effectively at scale.

Make an impact by building a high-performing Data Science and Machine Learning (ML) Engineering capability that drives innovation and business outcomes through AI and advanced analytics.

Responsibilities Own the end-to-end Data Science and AI agenda, delivering scalable models, AI systems, and agentic workflows embedded within decision-making across the Hub.

Oversee the design, build, and deployment of models and AI solutions into production environments to deliver reliable, high-performing outcomes that support business objectives at scale.

Establish and enforce standards for model development, MLOps, monitoring, and lifecycle management.

Partner with Analytics, Product, and Technology teams to translate decision strategies into automated, production-grade solutions with technical feasibility, scalability, and integrity.

Build and lead a multi-disciplinary Data Science capability, encompassing Data Scientists, ML Engineers, and MLOps specialists, ensuring strong technical depth, continuous development, and clear progression across the function.

Act as the single-threaded owner for the automation of decision-making, translating analytical logic and decision strategies into production-grade models and AI systems across the full lifecycle.

Oversee model performance, including accuracy, stability, drift, reliability, and real-world effectiveness of decision-making in production environments.

Embed controls, validation, monitoring, and safeguards into models and AI systems by design.

Advance AI and ML capabilities, including agentic AI, Large Language Model (LLM) use cases, MLOps, and automation frameworks, while increasing automation without adding risk or control debt.

Design scalable architectures, standardized pipelines, and reusable model components to enable efficient and repeatable delivery.

Build a high-performing Data Science, ML Engineering, and MLOps function, driving technical excellence, innovation, and career development.

Ensure models are explainable, traceable, auditable, and compliant with governance frameworks, partnering with Model Risk on technical implementation and model behaviour.

Qualifications Extensive experience leading engineering-grade Data Science and AI capabilities, delivering scalable, automated decisioning systems.

Proven track record of designing and deploying AI-driven solutions, leveraging advanced modelling techniques and emerging approaches such as LLMs and agentic workflows.

Ability to lead the delivery of production-grade AI solutions in a complex, regulated environment; provides technical leadership, fosters high-performing teams, and drives innovation while maintaining governance and risk management practices.

Experience working within financial crime or fraud environments is preferred.

Deep expertise in model development and lifecycle management, including building, deploying, monitoring, retraining, and retiring models in production environments.

Strong knowledge of MLOps, model monitoring, and production systems, ensuring reliability and operational effectiveness of models and automated decisioning.

Experience working in regulated environments with understanding of model governance, explainability, auditability, and data risk management.

Proven ability to build and scale high-performing teams across Data Science, ML Engineering, and MLOps functions.

Hours35Job Posting Closing Date19/07/2026Ways of Working Hybrid #J-18808-Ljbffr